output-validationv0.1.0

Automated validation of interval labels and mask outputs in video annotation pipelines. Ensures every key follows start->end format, frame indices are within video range, and CSR matrix integrity for each frame, reducing manual review.

Self-check of perception system outputs like object masks and lane markings before submission to downstream planning modules. Verifies mask shape consistency with camera resolution, CSR structure correctness, and frame count alignment with sampling policy.

Validation of segmentation masks and interval annotations for medical videos or scans. Checks that frame indices are within patient scan length, mask keys and values are correctly formatted, and CSR integrity for each slice.

Ensures correctness of robot visual instruction outputs (e.g., grasp regions) before execution. Validates mask consistency with camera resolution, frame coverage, and label validity to prevent runtime errors.

Offer basic video annotation tools for free, and charge for the output-validation skill as a premium plugin that ensures data quality for professional use.

Provide output-validation as a cloud API call, charging per validation run. Companies integrate it into their annotation pipelines to automatically check outputs before hand-off.

Include output-validation as a built-in feature of a comprehensive annotation platform. Charge higher subscription fees for platforms that include automated quality checks, reducing client manual review costs.